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<p>Objective functions for optimization. </p>
<p>In shark, the learning problem is phrased as an objective function which is then optimized using <a class="el" href="group__optimizers.html">Algorithms to find a local minimum of<a class="el" href="group__objfunctions.html">Objective functions</a>.</a> . This allows to test and develop algorithms using <a class="el" href="group__benchmarks.html">Benchmark functions</a> independent of the problem to solve. </p>
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Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_objective_function.html">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Super class of all objective functions for optimization and learning.  <a href="classshark_1_1_abstract_objective_function.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_combined_objective_function.html">shark::CombinedObjectiveFunction&lt; SearchPointType, ResultT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Linear combination of objective functions.  <a href="classshark_1_1_combined_objective_function.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_cross_validation_error.html">shark::CrossValidationError&lt; ModelTypeT, LabelTypeT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Cross-validation error for selection of hyper-parameters.  <a href="classshark_1_1_cross_validation_error.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_error_function.html">shark::ErrorFunction&lt; SearchPointType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Objective function for supervised learning.  <a href="classshark_1_1_error_function.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_evaluation_archive.html">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Objective function wrapper storing all function evaluations.  <a href="classshark_1_1_evaluation_archive.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_loo_error.html">shark::LooError&lt; ModelTypeT, LabelType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Leave-one-out error objective function.  <a href="classshark_1_1_loo_error.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_negative_log_likelihood.html">shark::NegativeLogLikelihood</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the negative log likelihood of a dataset under a model.  <a href="classshark_1_1_negative_log_likelihood.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_one_norm_regularizer.html">shark::OneNormRegularizer&lt; SearchPointType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">One-norm of the input as an objective function.  <a href="classshark_1_1_one_norm_regularizer.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_two_norm_regularizer.html">shark::TwoNormRegularizer&lt; SearchPointType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Two-norm of the input as an objective function.  <a href="classshark_1_1_two_norm_regularizer.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_variational_autoencoder_error.html">shark::VariationalAutoencoderError&lt; SearchPointType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the variational autoencoder error function.  <a href="classshark_1_1_variational_autoencoder_error.html#details">More...</a><br /></td></tr>
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Modules</h2></td></tr>
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<tr class="memdesc:group__constraint__handling"><td class="mdescLeft">&#160;</td><td class="mdescRight">Objects for handling constraints. <br /></td></tr>
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<tr class="memitem:group__benchmarks" id="r_group__benchmarks"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="group__benchmarks.html">Benchmark functions</a></td></tr>
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<tr class="memitem:group__kerneloptimization" id="r_group__kerneloptimization"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="group__kerneloptimization.html">Kernel Optimization</a></td></tr>
<tr class="memdesc:group__kerneloptimization"><td class="mdescLeft">&#160;</td><td class="mdescRight">All kinds of objective functions to optimize kernel functions. <br /></td></tr>
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